An Overview of Shallow and Deep Natural Language Processing for Ontology Learning A Zouaq – Ontology Learning and Knowledge Discovery Using …, 2011 – igi-global.com Abstract This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques for knowledge extraction from text, namely shallow techniques and deep techniques, and explains their … Cited by 6 Related articles All 2 versions

Automatic Short Essay Scoring Using Natural Language Processing to Extract Semantic Information in the Form of Propositions D Kerr, H Mousavi, M Iseli – CRESST Report, 2013 – semscape.cs.ucla.edu … In this paper, we introduce a novel technique for using domain-independent, deep natural language processing techniques to automatically extract meaning from student essays in the form of propositions and match the extracted propositions to the expected response. … Cited by 1 Related articles

Deep Natural Language Processing for Italian Sign Language Translation A Mazzei, L Lesmo, C Battaglino, M Vendrame… – AI* IA 2013: Advances in …, 2013 – Springer Abstract This paper presents the architecture of a translator from written Italian into Italian Sign Language. We describe the main features of the four modules of this architecture, ie a dependency parser for Italian, an ontology based semantic interpreter, a generator based … Related articles All 2 versions

A corpus of clinical narratives annotated with temporal information L Galescu, N Blaylock – Proceedings of the 2nd ACM SIGHIT …, 2012 – dl.acm.org … We are working to- wards applying deep Natural Language Processing tools to- wards understanding such narratives. This requires both the extraction and classification of the relevant events, and the placing of those events in time, or at least in relation to one another. … Cited by 9 Related articles All 13 versions

Why we need evolutionary semantics L Steels – KI 2011: Advances in Artificial Intelligence, 2011 – Springer … This approach stands in contrast to the one explored in earlier deep natural language processing research which used sophisticated grammars based on linguistic the- ory and procedural semantics for the precise interpretation of meaning in terms of world models derived from … Cited by 1 Related articles All 8 versions

Mining Semi-Structured Online Knowledge Bases to Answer Natural Language Questions on Community QA Websites P Sondhi, CX Zhai – Proceedings of the 23rd ACM International …, 2014 – dl.acm.org … How- ever most of these approaches are designed to answer only a restricted set of questions such as short and precise fac- toid [3] or definitional [5]. In addition they tend to require deep natural language processing steps such as generation of parse trees to analyze the …

Instructor-aided asynchronous question answering system for online education and distance learning D Wen, J Cuzzola, L Brown – The International Review of Research in …, 2012 – irrodl.org … However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. … Cited by 1 Related articles All 5 versions

Making Watson fast EA Epstein, MI Schor, BS Iyer, A Lally… – IBM Journal of …, 2012 – ieeexplore.ieee.org … This paper describes how a large set of deep natural-language processing programs were integrated into a single application, scaled out across thousands of central processing unit cores, and optimized to run fast enough to compete in live Jeopardy!i games. … Cited by 11 Related articles All 3 versions

Text Summarization in Android Mobile Devices OM Foong, SP Yong, AL Lee – … of the First International Conference on …, 2014 – Springer … produce shorter summarized text. Most researchers applied extractive summary as it is more difficult to develop abstractive summary due to its implementation of deep natural language processing. The main challenge would … Related articles

Grounding Language through Evolutionary Language Games L Steels – Language Grounding in Robots, 2012 – Springer … This approach stands in contrast to the one explored in earlier deep natural language processing research which used sophisticated grammars based on linguistic theory and procedural semantics for the precise interpretation of meaning in terms of world models derived from … Cited by 8 Related articles All 6 versions

Selecting answers to questions from Web documents by a robust validation process A Grappy, B Grau, MH Falco, AL Ligozat… – Proceedings of the …, 2011 – dl.acm.org … questions. Best systems make use of deep Natural Language Processing (NLP) techniques, in order to match questions and candidate passages and extract answers [1], [2], [3] for some European languages and [4] for French. … Cited by 12 Related articles All 11 versions

Multi-Entity Polarity Analysis in Financial Documents JZ Ferreira, J Rodrigues, M Cristo… – Proceedings of the 20th …, 2014 – dl.acm.org … We evaluated models based on the partition of documents into fragments according to the en- tities they cite. We used several heuristics to segment documents based on shallow and deep natural language processing (NLP). …

Tapping Into The Power of Automatic Scoring WH Gomaa, AA Fahmy – the eleventh International Conference on …, 2011 – researchgate.net … C-rater’s technology uses “bag of words approach” in which deep natural language processing is used to assess whether a student response contains text which could be considered a paraphrase of the concepts listed in the rubric for an item. … Cited by 1 Related articles

Towards web search by sentence queries: asking the web for query substitutions Y Yamamoto, K Tanaka – Database Systems for Advanced Applications, 2011 – Springer … expressions for written language to ones for spoken language based on oc- currence in written and spoken language corpora [5]. As in these studies, most approaches are based on off-line processing through machine learning or deep natural-language processing, and they … Cited by 1 Related articles All 5 versions

Short Answer Grading Using String Similarity and Corpus-Based Similarity WH Gomaa, AA Fahmy – International Journal of Advanced …, 2012 – researchgate.net … accuracy for short answer responses. The reason behind high accuracy is using deep natural language processing to determine the relatedness of student response to the concepts listed in the rubric for an item. The C-rater engine … Cited by 2 Related articles All 6 versions

Automated learning of social ontologies K Kotis, A Papasalouros – … and Knowledge Discovery Using the Web: …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 1 Related articles All 2 versions

Transforming a Flat Metadata Schema to a Semantic Web Ontology: The Polish Digital Libraries Federation and CIDOC CRM Case Study C Mazurek, K Sielski, M Stroi?ski, J Walkowska… – Intelligent Tools for …, 2012 – Springer … In some cases a more meaningful table of contents might be built based on different kinds of relations (dc:relation and its subelements, especially dcterms:hasPart). Future works allowing to achieve more meaningful mapping should include deep natural language processing. … Cited by 12 Related articles All 4 versions

Exploring the Potential of Speech Recognition to Support Problem Solving and Reflection M Mavrikis, B Grawemeyer, A Hansen… – Open Learning and …, 2014 – Springer … process in an effort to respond on the system’s prompts. As the wizards were avoiding performing deep natural language processing they could not help the students. We observed similar situations in the recordings of the rest …

A Labeled Graph Kernel for Relationship Extraction G Simões, H Galhardas, D Matos – arXiv preprint arXiv:1302.4874, 2013 – arxiv.org … limited size around them. The advantage of this kernel is its simplicity since it does not need deep Natural Language Processing tools to preprocess the sentences in order to compute the kernel. However, its major advantage … Cited by 1 Related articles All 2 versions

Sequential pattern based multi document summarization—An exploratory approach S Alias, SK Muhammad – Research and Innovation in …, 2013 – ieeexplore.ieee.org … of two similarity measures. Going into deep Natural Language Processing, [9] analyzed the Discourse Structure of the text in order to produce a coherence summary by using Lexical or coreference chain. Here, the main topics … Related articles

Named entity recognition and identification for finding the owner of a home page V Plachouras, M Rivière, M Vazirgiannis – Advances in Knowledge …, 2012 – Springer … Minkow et al. [11] apply a CRF model to recognize names in emails, using features which are primarily based on gazetteers for per- son first and last names, names of organizations and locations, but not using deep natural language processing. Zhu et al. … Cited by 1 Related articles All 3 versions

The Era of Cognitive Systems: An Inside Look at IBM Watson and How it Works R High – Redguites for Business Leaders, 2012 – developer.ibm.com … rule. They might be precise, but not necessarily very accurate. Deep natural language processing To overcome the limitations of brick building, we shifted to using steel and reinforced concrete for larger buildings. Likewise, we … Cited by 2 Related articles All 6 versions

[BOOK] Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances W Wong, W Liu, M Bennamoun, IGI Global – 2011 – eprint13.blacknight.ie Page 1. Wilson Wong The University of Western Australia, Australia Wei Liu The University of Western Australia, Australia Mohammed Bennamoun The University of Western Australia, Australia Ontology Learning and Knowledge Discovery Using the Web: … Cited by 3 Related articles All 5 versions

Extracting Summary from Documents using K-mean Clustering Algorithm DVS Ramana – IJCSNS, 2014 – paper.ijcsns.org … MMR approach used earlier. The advantages of the introduced method are: it does not use external resource except the original document given summary and deep natural language processing is not required. This method has …

Multi-Document Summarization Based On Sentence Clustering Improved Using Topic Words I Lukmana, D Swanjaya, A Kurniawardhani… – JUTI: Jurnal Ilmiah …, 2014 – juti.if.its.ac.id … An abstractive summarization can produce summaries that are more like what a human might generate but it requires deep natural language processing techniques [1]. Because of simple but robust method for text summarization, most of multi-document summarization focus on …

DESAMC+ DocSum: Differential evolution with self-adaptive mutation and crossover parameters for multi-document summarization RM Alguliev, RM Aliguliyev, NR Isazade – Knowledge-Based Systems, 2012 – Elsevier … Abstraction can be described as reading and understanding the text to recognize its content that is then compiled in a concise text [37]. Although an abstractive summary could be more concise, it requires deep natural language processing (NLP) techniques. … Cited by 13 Related articles All 3 versions

Utilizing graph-based representation of text in a hybrid approach to multiple documents summarization MA Sayed – 2014 – dar.aucegypt.edu Page 1. All Rights Reserved. This work may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author. SCHOOL OF SCIENCES AND ENGINEERING Utilizing Graph-based Representation of Text in a Hybrid … Related articles

Domain-sensitive topic management in a modular conversational agent framework D Macias Galindo – 2014 – researchbank.rmit.edu.au … Modularity can range from additional knowledge domains to new capabilities or behaviours of the Toy, such as story-telling or becoming a math tutor. Regarding its conversational capabilities, the Toy does not perform deep natural language processing over user inputs. …